Federated analysis of BRCA1 and BRCA2 variation in a Japanese cohort

• Published in: Cell genomics 2022-03, Vol.2 (3), p.100109, Article 100109
• Main Authors: Casaletto, James, Parsons, Michael, Markello, Charles, Iwasaki, Yusuke, Momozawa, Yukihide, Spurdle, Amanda B., Cline, Melissa
• Format: Article
• Language: English
• Subjects: benign; co-occurrence analysis; data privacy; federated computing; pathogenic; variant classification; Variant of uncertain significance
• ISSN: 2666-979X; 2666-979X
• DOI: 10.1016/j.xgen.2022.100109

More than 40% of the germline variants in ClinVar today are variants of uncertain significance (VUSs). These variants remain unclassified in part because the patient-level data needed for their interpretation is siloed. Federated analysis can overcome this problem by “bringing the code to the data”: analyzing the sensitive patient-level data computationally within its secure home institution and providing researchers with valuable insights from data that would not otherwise be accessible. We tested this principle with a federated analysis of breast cancer clinical data at RIKEN, derived from the BioBank Japan repository. We were able to analyze these data within RIKEN’s secure computational framework without the need to transfer the data, gathering evidence for the interpretation of several variants. This exercise represents an approach to help realize the core charter of the Global Alliance for Genomics and Health (GA4GH): to responsibly share genomic data for the benefit of human health. [Display omitted] Federated methods enable scientific analysis of privacy-sensitive dataFederated co-occurrence enabled novel BRCA genotype and phenotype assessmentOur federated methods are generalizable to other genes, phenotypes, and file formatsThis approach can be applied to other sensitive data analyses such as family studies Casaletto et al. developed containerized methods to analyze sensitive data without compromising the privacy of the original study participants. Co-occurrence of unclassified variants with known pathogenic ones provides evidence of being benign. This research serves as a proof-of-concept that is generalizable to other data types, file formats, and bioinformatic analyses.